Code (pytorch) for 'Source-Free Domain Adaptation via Target Prediction Distribution Search' on Digits(MNIST, USPS, SVHN), Office-31, Office-Home, VisDA-C, PACS. This paper has been accepted by International Journal of Computer Vision (IJCV). DOI: https://doi.org/10.1007/s11263-023-01892-w
You need to download the MNIST,USPS,SVHN,Office-31, Office-Home,PACS, VisDA-C dataset, modify the path of images in each '.txt' under the folder './data/'.
The experiments are conducted on one GPU (NVIDIA RTX TITAN).
- python == 3.7.3
- pytorch ==1.6.0
- torchvision == 0.7.0
Please refer to the file on run.sh.
Tang, S., Chang, A., Zhang, F. et al. Source-Free Domain Adaptation via Target Prediction Distribution Searching. Int J Comput Vis (2023). https://doi.org/10.1007/s11263-023-01892-w
The code is based on DeepCluster(ECCV 2018) , SHOT (ICML 2020, also source-free) and IIC.